Text sentiment classification aims to automatically classify subjective documents into different sentiment-oriented categories (e.g. positive/negative). Given the high dimensionality of features describing documents, how to effectively select the most useful ones, referred to as sentiment-bearing features, with a lack of sentiment class labels is crucial for improving the classification performance. This paper proposes an unsupervised sentiment-bearing feature selection method (USFS), which incorporates sentiment discriminant analysis (SDA) into sentiment strength calculation (SSC). SDA applies traditional linear discriminant analysis (LDA) in an unsupervised manner without losing local sentiment information between documents. We use SSC to calculate the overall sentiment strength for each single feature based on its affinities with some sentiment priors. Experiments, performed using benchmark movie reviews, demonstrated the superior performance of USFS.

The joint representations of knowledge graph have become an important approach to improve the quality of knowledge graph, which is beneficial to machine learning, data mining, and artificial intelligence applications. However, the previous work suffers severely from the noise in text when modeling the text information. To overcome this problem, this paper mines the high-quality reference sentences of the entities in the knowledge graph, to enhance the representation ability of the entities. A novel framework for joint representation learning of knowledge graphs and text information based on reference sentence noise-reduction is proposed, which embeds the entity, the relations, and the words into a unified vector space. The proposed framework consists of knowledge graph representation learning module, textual relation representation learning module, and textual entity representation learning module. Experiments on entity prediction, relation prediction, and triple classification tasks are conducted, results show that the proposed framework can significantly improve the performance of mining and fusing the text information. Especially, compared with the state-of-the-art method[15], the proposed framework improves the metric of H@10 by 5.08% and 3.93% in entity prediction task and relation prediction task, respectively, and improves the metric of accuracy by 5.08% in triple classification task.

Numerous studies have shown that scaling exponents of internet traffic change over time or scaling ranges. In order to analyze long-range dependent traffic with changing scaling exponents over time scales, we propose a multi-scale traffic model that incorporates the notion of a piecewise self-similar process, a process with spectral changes on its scaling behavior. We can obtain a performance curve smoothened over the range of queue length corresponding to time scales with different scaling exponents by adopting multiple self-similar processes piecewise into different spectra of time scale. The analytical method for the multiscale fractional Brownian motion is discussed as a model for this approach. A comparison of the analytical and simulation results, using traffic data obtained from backbone networks, shows that our model provides a good approximation for Gaussian traffic.

Since Smart Antenna technology has powerful spatial processing ability; it is regarded as a promising approach to enhancing the data rates and capacity of wireless LAN systems. In this paper, a small size, practical switched-beam antenna system, well suited for domestic in-home networking in the 2.4 GHz band, is designed and tested. The system has the configuration of regular nine-prism, and nine 1/4 wavelength rectangular patches are symmetrically distributed on the nine sides of the prism. The switching process is based on control of the microstrip used to feed the patch radiators, by placing PIN diodes at the microstrip feeding lines. The antenna array can generate nine beams with a gain of 11 dB. All the beams generated by the system are cophasal excited and have a 40°beamwidth. Compared to the uniform array, the system can guarantee the consistency of every beam and is preferable in shape.

With the increasing popularity of multicast and real-time streaming service applications, efficient channel assignment algorithms that handle both multicast and unicast traffic in wireless mesh networks are needed. One of the most effective approaches to enhance the capacity of wireless networks is to use systems with multiple channels and multiple radio interfaces. However, most of the past works focus on vertex coloring of a general contention graph, which is NP-Complete, and use the greedy algorithm to achieve a suboptimal result. In this paper, we combine unicast and multicast with a transmission set, and propose a framework named Chordal Graph Based Channel Assignment (CGCA) that performs channel assignment for multicast and unicast traffic in multi-channel multi-radio wireless mesh networks. The proposed framework based on chordal graph coloring minimizes the interference of the network and prevents unicast traffic from starvation. Simulation results show that our framework provides high throughput and low end-to-end delay for both multicast and unicast traffic. Furthermore, our framework significantly outperforms other well-known schemes that have a similar objective in various scenarios.

The integration of multihop relays with orthogonal frequency-division multiple access (OFDMA) cellular infrastructures can meet the growing demands for better coverage and higher throughput. Resource allocation in the OFDMA two-hop relay system is more complex than that in the conventional single-hop OFDMA system. With time division between transmissions from the base station (BS) and those from relay stations (RSs), fixed partitioning of the BS subframe and RS subframes can not adapt to various traffic demands. Moreover, single-hop scheduling algorithms can not be used directly in the two-hop system. Therefore, we propose a semi-distributed algorithm called ASP to adjust the length of every subframe adaptively, and suggest two ways to extend single-hop scheduling algorithms into multihop scenarios: link-based and end-to-end approaches. Simulation results indicate that the ASP algorithm increases system utilization and fairness. The max carrier-to-interference ratio (Max C/I) and proportional fairness (PF) scheduling algorithms extended using the end-to-end approach obtain higher throughput than those using the link-based approach, but at the expense of more overhead for information exchange between the BS and RSs. The resource allocation scheme using ASP and end-to-end PF scheduling achieves a tradeoff between system throughput maximization and fairness.

The voltage biased SQUID Bootstrap Circuit (SBC) was recently demonstrated for direct readout of SQUID signals. The SBC combines current- and voltage-feedbacks in one circuit to suppress the preamplifier noise. It offers not only a good noise performance, but also wide tolerance of SQUID parameters. Using SBC gradiometer, the bio-magnetic signals were successfully measured. In this paper, we overview the concept of SBC and its applications.

This paper proposes an advanced hybrid network architecture and a comprehensive network design of the next-generation science information network, called SINET3. Effectively combining layer-1 switches and IP/MPLS routers, the network provides layer-1 end-to-end circuit services as well as IP and Ethernet services and enables flexible resource allocation in response to service demands. The detailed network design focuses on the tangible achievement of providing a wide range of network services, such as multiple layer services, multiple virtual private network services, advanced qualities of service, and layer-1 bandwidth on demand services. It also covers high-availability capabilities and effective resource assignment in the hybrid network. The cost reduction effect of our network architecture is also shown in this paper.

Detecting a variety of anomalies caused by attacks or accidents in computer networks has been one of the real challenges for both researchers and network operators. An effective technique that could quickly and accurately detect a wide range of anomalies would be able to prevent serious consequences for system security or reliability. In this article, we characterize detection techniques on the basis of learning models and propose an unsupervised learning model for real-time anomaly detection in computer networks. We also conducted a series of experiments to examine capabilities of the proposed model by employing three well-known machine learning algorithms, namely multivariate normal distribution, k-nearest neighbor, and one-class support vector machine. The results of these experiments on real network traffic suggest that the proposed model is a promising solution and has a number of flexible capabilities to detect several types of anomalies in real time.

Networking technologies have recently been evolving and network applications are now expected to support flexible composition of upper-layer network services, such as security, QoS, or personal firewall. We propose a multi-platform framework called FreeNA* that extends existing applications by incorporating the services based on user definitions. This extension does not require users to modify their systems at all. Therefore, FreeNA is valuable for experimental system usage. We implemented FreeNA on both Linux and Microsoft Windows operating systems, and evaluated their functionality and performance. In this paper, we describe the design and implementation of FreeNA including details on how to insert network services into existing applications and how to create services in a multi-platform environment. We also give an example implementation of a service with SSL, a functionality comparison with relevant systems, and our performance evaluation results. The results show that FreeNA offers finer configurability, composability, and usability than other similar systems. We also show that the throughput degradation of transparent service insertion is 2% at most compared with a method of directly inserting such services into applications.

Cognitive radio ad hoc networks can be used to solve the problems of limited available spectrum and inefficient spectrum usage by adaptively changing their transmission parameters. Routing protocol design has a significant impact on the network performance. However, an efficient protocol that takes account of primary user flows and the long-term channel assignment issue in route selection is still missing. In this paper, we propose AODV-cog, a cognitive routing protocol for CSMA/CA ad hoc networks based on AODV. AODV-cog chooses a route by considering the effect on the primary users, available channel bandwidth and link reliability. AODV-cog also takes account of future channel utilization which is an important but underexplored issue. AODV-cog switches channels for secondary user flows when network congestion occurs. We use theoretical analysis and computer simulations to show the advantage of AODV-cog over existing alternatives.

Multiple-antenna wireless systems, also known as multiple-input multiple-output (MIMO) cellular networks, can improve the capacity and reliability of communications. To realize these advantages, a packet scheduler should effectively allocate radio resources to users in a fair way. The previously proposed MIMO schedulers have problems such as ignoring traffic arrival process or complexity. We propose a load adaptive multi-output fair queueing (LA-MO-FQ) scheduler, which is based on a fair queueing algorithm with mechanisms for rate selection, compensation of lagging users, and virtual time system. Since some of the scheduler's system parameters are sensitive to the traffic load, it dynamically adjusts them in a way with low complexity so the system performs better. Intensive simulation studies considering the mobility of users and the traffic arrival demonstrate the good performance of LA-MO-FQ. Furthermore, we also propose in this paper some formulae for the time and service fairness comparisons of MIMO schedulers and we use them for comparison with some famous existing schedulers.

Authentication issue has been mostly ignored to ensure fast handoff in 802.11 Wireless Mesh Network (WMN). With the proliferation of WMNs in recent years for practical deployment, secured fast handoff has drawn much attention to enforce authenticated access while reduce the extra delay caused by enabling authentication operations. In this paper, we present an overview on the state-of-the-art advance in this field and tackle the problem from a practical perspective based on experiments and analysis on our real-world testbed HAWK. We propose a novel fast handoff scheme Network-assisted Radio Signature to eliminate probing delay by taking advantage of the characteristic of the actual dynamic topology about mesh routers in WMN. Moreover, we apply an optimistic authentication mechanism Dual Re-authentication to counteract the authentication delay while providing the secured wireless access. In this manner, we have reduced the end-to-end handoff delay of WMN back again to a level below 50 ms to achieve secured handoff and support time-sensitive applications. We describe detailed mechanisms, simulation, implementation and experimental results. To our best knowledge, we are the first to achieve such an optimal performance of secured fast handoff.

Wireless sensor network MAC protocols switch radios off periodically, employing the so-called duty cycle mechanism, in order to conserve battery power that would otherwise be wasted by energy-costly idle listening. In order to minimize the various negative side-effects of the original scheme, especially on latency and throughput, various improvements have been proposed. In this paper, we introduce a new MAC protocol called MAC2(Multi-hop Adaptive with packet Concatenation-MAC) which combines three promising techniques into one protocol. Firstly, the idea to forward packets over multiple hops within one operational cycle as initially introduced in RMAC. Secondly, an adaptive method that adjusts the listening period according to traffic load minimizing idle listening. Thirdly, a packet concatenation scheme that not only increases throughput but also reduces power consumption that would otherwise be incurred by additional control packets. Furthermore, MAC2 incorporates the idea of scheduling data transmissions with minimum latency, thereby performing packet concatenation together with the multi-hop transmission mechanism in a most efficient way. We evaluated MAC2 using the prominent network simulator ns-2 and the results show that our protocol can outperform DW-MAC – a state of the art protocol both in terms of energy efficiency and throughput.

Relay has been incorporated into standards of wireless access networks to improve the system capacity and coverage. However, the resource allocation problem to support scalable video coding (SVC) multicast for wireless relay networks is challenging due to the existence of relay stations (RSs). In this paper, we study the resource allocation problem for SVC multicast over multi-hop wireless relay networks to maximize the total utility of all users with a general non-negative, non-decreasing utility function. Since the problem is NP-hard, we simplify it with RS specification functions which specialize the relay station to receive data for each user, and convert the resource allocation problem with one RS specification function as finding a maximum spanning sub-tree of a directed graph under budget constraint. A heuristic algorithm is proposed to solve the problem with polynomial time complexity. The simulation results reveal that the proposed algorithm outperforms other algorithms under assumptions of two-hop wireless relay networks or separated transmission for relay and access links, and it keeps good approximation to the optimal results.

We conduct, in accordance with IEC 61000-4-2, an electrostatic discharge (ESD) test for a small size battery-operated control circuit board in a myoelectric artificial hand system to investigate the influence of the induced noises by indirect ESDs from an ESD generator to a horizontal coupling plane (HCP) and a vertical coupling plane (VCP). A photo-coupler is set between the small size control board and a motor control circuit to suppress noise in the pulse width modulation (PWM) signals. Two types of ESD noise are observed at the output pins of PWM signals. One type is the ESD noise itself (called Type A) and the other one is the ESD noise superimposed over the PWM pulses (Type B). No matter which polarity the charge voltages of the ESD generator have, both types can be observed and the Type A is dominant in the output pulses. Moreover, the ESD interference in the HCP case is found to be stronger than that in the VCP case usually. In the PWM signals observed at the photo-coupler output, on the other hand, Type A noises tend to increase for positive polarity and decrease for negative polarity, while Type B noises tend to increase at -8kV test level in the HCP case. These results suggest that the photo-coupler does not work well for ESD noise suppression. One of the reasons has been demonstrated to be due to the driving capability of the photo-coupler, and other one is due to the presence of a parasitic capacitance between the input and output of the photo-coupler. The parasitic capacitance can yield a capacitive coupling so that high-frequency ESD noises pass through the photo-coupler.

The wideband noise controlling performance of the delayless subband adaptive filtering technique is affected by the group delay and in-band aliasing distortion of analysis filter banks. A method of recursive second-order cone programming is proposed to design the uniform DFT modulated analysis filter banks, with a small in-band aliasing error and low group delay. Simulation results show that the noise controlling performance is improved with small residual noise power spectra, a high noise attenuation level and fast convergence rate.

How to manage the video streaming in future networks is becoming a more and more challenging issue. Recent studies on vehicular networks depict a new picture of the next generation Intelligent Transport System (ITS), with high level road safety and more comfortable driving experience. To cope with the heterogeneous network development for the next generation cellular network, centralized medium control is promising to be employed upon Road Side Unit (RSU). To accommodate the QoS constraints posed by video services in vehicular networks, the scalable video coding (SVC) scheme in H.264/AVC standard family offers spatial and temporal scalabilities in the video dissemination. In this paper, we target the resource allocation and layer selection problem for the multi-user video streaming over highway scenario, by employing SVC coding scheme for the video contents. We propose a Resource Allocation and Layer Selection (RALS) algorithm, which explicitly takes account of the utility value of each Group Of Picture (GOP) among all the vehicular users. Simulation results show that our proposed RALS algorithm outperforms the comparison schemes in typical scenarios.

Optical Burst Switching (OBS) has been developed as an efficient switching technique to exploit the capacity provided by Wavelength Division Multiplexing (WDM) transmission technology for the next generation optical Internet. One critical design issue in OBS is how to provide Quality-of-Service (QoS) on optical networks. In order to provide the service differentiation, we propose in this paper a buffer allocation algorithm to schedule bursts at the edge OBS nodes, a bandwidth allocation algorithm and a Fiber Delay Line (FDL) allocation algorithm to schedule bursts at the core OBS nodes. We also introduce a new burst assembly technique in which the burst is generated either when the sum of the collected packet sizes reaches the maximum threshold or when the burst assembling time reaches the timeout limit. Our simulation results show that the proposed algorithms achieve the controllable burst loss probability for different service classes. The bandwidth allocation algorithm performs very well at the core OBS nodes in terms of the low loss probability.